Tagged: Big Data

Gaming democracy

Not far short of three years-ago I published a piece on the Huffington Post which suggested that humans had moved from the age of the sword into the age of the printing press and were about to move into the age of the algorithm. The reason, I suggested, for why a particular form of technology came to shape an age was that each technology conferred an advantage upon an elite or institutionalised group, or at least facilitated the emergence of a such group which could control these technologies in order to achieve dominance.

This is why the algorithm will have its age. Algorithms are extraordinarily powerful but they are difficult things to create. They require highly paid geeks and therefore their competitive advantage will be conferred on those with the greatest personal or institutionalised resource – billionaires, the Russians, billionaire Russians, billionaire Presidents (Russian or otherwise). There is also a seductive attraction between algorithms and subterfuge: they work most effectively when they are invisible. Continue reading

Google: the United States of Data

A couple of weeks ago I stumbled across something called Google Big Query and it has changed my view on data. Up until that point I had seen data (and Big Data) as something both incredibly important and incredibly remote and inaccessible (at least for an arts graduate). However, when I checked-out Google Big Query I suddenly caught a glimpse of a future where an arts graduate can become a data scientist.

Google Big Query is a classic Google play in that it takes something difficult and complicated and rehabilitates it into the world of the everyday. I can’t pretend I really understood how to use Google Big Query, but I got the strong sense that I wasn’t a million miles away from getting that understanding – especially if GBQ itself became a little more simplified.

And that presents the opportunity to create a world where the ability to play with data is a competence that is available to everyone. Google Big Query could become a tool as familiar to the business world as PowerPoint or Excel. Data manipulation and interrogation will become a basic business competence, not just a rarefied skill.

The catch, of course, is that this opportunity is only available to you once you have surrendered your data to the Google Cloud (i.e. to Google) and paid for an entry visa. As it shall at the base of the Statue of Googlability that marks the entry point to the US of D:

“Give me your spreadsheets, your files,
Your huddled databases yearning to breathe free,
The wretched data refuse of your teeming shore.
Send these, the officeless, ppt-tossed, to me:
I lift my algorithms beside the (proprietary) golden door.”

And the rest, as they say, shall be history (and a massive future revenue stream).

Is the bulk interception of data actually worse than mass surveillance?

Where does bulk interception of data stop and mass surveillance start and in the world of Big Data and algorithmic surveillance is it even relevant to make such a distinction?

It emerged last week that these are important questions, following a ruling by the UK’s Investigatory Powers Tribunal and subsequent response by the UK government and its electronic spying outfit, GCHQ (see the details in this Guardian report).  This response proposes that mass surveillance doesn’t really happen (even if it may look a bit like it does), because all that is really going on is bulk interception of data and this is OK (and thus can be allowed to happen).

One of the most disturbing revelations flowing from Edward Snowden’s exposure of the Prism and Upstream digital surveillance operations is the extent to which the US and UK governments have been capturing and storing vast amounts of information, not just on possible terrorists or criminals, but on everyone. This happened in secret and its exposure has eventually prompted a response from government and this response has been to assert that this collection and storage doesn’t constitute mass surveillance, instead it is “the bulk interception of data which is necessary to carry out targeted searches of data in pursuit of terrorist or criminal activity.”

This is the needle in the haystack argument – i.e. we need to process a certain amount of everyone’s hay in order to find the terrorist needles that are hidden within it. This seems like a reasonable justification because it implies that the hay (i.e. the information about all of us) is a disposable asset, something to be got rid of in order to expose the needles. This is basically the way that surveillance has always operated. To introduce another analogy, it is a trawling operation that is not interested in the water that passes through the net only the fish that it contains.

However, this justification falls down because this is not the way that algorithmic surveillance works. Algorithmic surveillance works by Continue reading

In a datafied world, algorithms become the genes of society

Here is an interesting and slightly scary thought.  What is currently going on (in the world of Big Data) is a process of datafication (as distinct from digitisation).  The secret to using Big Data is first constructing  a datafied map of the world you operate within.  A datafied map is a bit like a geological map, in that it is comprised of many layers, each one of which is a relevant dataset.  Algorithms are what you then use to create the connections between the layers of this map and thus understand, or shape, the topography of your world.  (This is basically Big Data in a nutshell).

In this respect, algorithms are a bit like genes.  They are the little, hidden bits of code  which none-the-less play a fundamental role in shaping the overall organism – be that organism ‘brand world’, ‘consumer world’, ‘citizen world’ or ‘The Actual World’ (i.e. society) – whatever world it is that has been datafied in the first place.  This is slightly scary, given that we are engaged in a sort of reverse human genome project at the moment: instead of trying to discover and expose these algorithmic genes and highlight their effects, the people making them are doing their best to hide them and cover their traces.  I have a theory that none of the people who really understand Big Data are actually talking about it – because if they did they are afraid someone will tell them to stop.  The only people giving the presentations on Big Data at the moment are small data people sensing a Big Business Opportunity.

But what gets more scary is if you marry this analogy (OK, it is only an analogy) to the work of Richard Dawkins.  It would be a secular marriage obviously.  Dawkins’ most important work in the field of evolutionary biology was defining the concept of the selfish gene.  This idea proposed (in fact proved I believe) that Darwin (or Darwinism) was not quite right in focusing on the concept of survival of the fittest, in that the real battle for survival was not really occuring between individual organisms, but between the genes contained within those organisms.  The fate of the organism was largely a secondary consequence of this conflict.

Apply this idea to a datafied society and you end up in a place where everything that happens in our world becomes a secondary consequence of a hidden struggle for survival between algorithms.  Cue Hollywood movie.

On a more immediate / practical level, this is a further reason why the exposure of algorithms and transparency must become a critical component of any regulatory framework for the world of Big Data (the world of the algorithm).

 

October engagements: Shel Holtz (#smwisoc) and Golden Drums

FireShot Screen Capture #180 - 'Strategic_digital_engagement_seminar-earlybird_pdf' - www_isoc_com_files_pages_Strategic_digital_engagement_seminar-earlybirdI have a couple of engagements in October I would like to flag.

First, social media guru Shel Holtz (@shelholtz) is going to be in the UK from 27-31 October for the week-long strategic digital engagement seminar organised by ISOC.  Since the poor man can’t be asked to provide an entire week’s worth of seminars, some others (Paul Marsden, Janet Murray and myself), have been hired as support acts.  I am going to be responsible for the future, as in Social Media and the Next Big Things: the Forces that will Shape the Social Digital Space in the Next Few Years.  It will focus on Big Data and the world of the algorithm in the morning and rise of communmity and why community may become the new media in the afternoon.

Should be fun.

Places on this one are pretty limited and also have a £2,200 price tag attached, so if you are interested please sign up here.

Second, although firstly chronologically speaking, I will be speaking on October 10 at the Golden Drums in Slovenia.  The organisers have allowed me to run a session (actually pitched as an EACA masterclass) called “An alternative look at content” which I am going to use as an opportunity to expose those guilty for filling the social digital space with Brandfill and reveal why they are doing it.

I think it unlikely you will travel to Slovenia just to listen to me, but if you do happen to be going anyway, my session is at 14.00 on Friday – and you will have the choice between me and Johan Jervøe, Group Chief Marketing Officer, UBS AG who will be answering the question “Branded content: has social media changed the world of creative excellence?”.  Not that I want to influence anyone, but I will also be answering that question.  In fact I can give you the answer now: yes, branded content and social media has changed the world of creative excellence, but only in-so-far as it is causing us to forget what creative excellence really is.  This is because most branded content is simply tediously long-form advertising, with all of the things that made advertising effective taken out of it.

I will also be giving away T-shirts.

 

 

 

Will Big Data kill Vendor Relationship Management?

Modernization of Al-Khalid Main Battle Tank (MBT) PAKISTAN ARMY I III have just finished reading Doc Searls’ Intention Economy. And about time too. The book has been out about two years and it is widely recognised as being a Very Important Book. In my defence, I have been following the Vendor Relationship Management (VRM) thing anyway and have even had some marginal contact with the good Doc himself on the issue. So it was more a case of filling-in the gaps. For those not already in the know, VRM is positioned as the counterpoint to CRM (Customer Relationship Management). CRM is how brands use data about their customers in order to define the relationship the brand decides it wants to have with the customer: VRM proposes that customers should own and control the data about themselves so that they can define the relationship they want to have with brands.

I can validate that it is indeed a Very Important Book because it not only defines this new and potentially interesting area (VRM) but also because it strays into a wider analysis of the history and operation (and philosophy) of the internet. The issues that it raises here are becoming increasingly important as pressures build to manage, regulate and appropriate the internet in order to make it conform to political or commercial vested interest. In fact, this wider analysis could turn out to be the most important aspect in the book, or perhaps a valid subject for a new book.

The Intention Economy and VRM is something I would very much like to believe in. Trouble is, form me VRM is a bit like God: something I would like to believe in if only I could get the evidence and reality to stack up. There seem to be just too many reasons why VRM (like God) doesn’t or won’t exist.   At one level, VRM appears to be overly reliant on a code-based answer. This is probably because Doc Searls himself and many of the current VRM gang come out of this place. But the concept that I found most interesting in the book was the idea of the things Doc calls ‘fourth parties’. Fourth parties are organisations that can aggregate customer intentions and thus create leverage and scale efficiencies. This takes us into the realm of community, which rings bells with me since I believe that within a few years almost all relationships between individuals and brands will be mediated by some form of community. In fact, this would be my own take on how the Intention Economy might actually come into being. I think it is the ability to connect individual customers, rather than empower them as individuals, that is likely to present the greatest opportunity to change the rules of the game – as things like TripAdvisor or even Airbnb are starting to demonstrate. However, fourth parties get relatively short shrift in the book, perhaps because they are not a code-based answer.

But my greatest area of scepticism, or perhaps fear, for the future of the customer and citizen, stems from the emerging world of Big Data and algorithms. As outlined in my previous post, algorithms suck the power out of the idea of having a personal data repository and make the ownership of this, from a government, brand, customer or citizen perspective largely irrelevant. In the world of the algorithm, your personal data file (i.e. your life) becomes little more than personal opinion. To all intents and purposes your ‘real’ identity is defined by the algorithm and the algorithm’s decision about who you are and how you shall be treated will pay scant attention to any information that is personal to you, other than to use it as a faint, initial signal to acquire ’lock-on’.

The problem with algorithms is that (like tanks) they favour governments and corporations. It is hard for a citizen to get a hold of, or be able to use, an algorithmic tank. And if you are standing in front of an algorithmic tank, giving you the rifle and flak-jacket of your own data isn’t much protection. It is why Wall Street is the first place that the world of the algorithm has really taken hold – it could afford the best geeks. And as Wall Street is showing, the world of the algorithm tends towards a very dark and opaque sort of place – about as far removed from the sun-lit commons of open-source code sharing as it is possible to be.

However, create the opportunity to connect a million people with rifles and flak-jackets to confront one algorithmic tank, and the odds get better. You may even be able to form a fourth party which can create its own tank, or at least some effective anti-tank weapons.

So, I guess my message to Doc Searls and the VRM gang would be: don’t loose faith in the idea of VRM and the Intention Economy as a destination, but think again about the route.  Build on the idea of fourth parties and focus on community and connection, rather than tools and code, and recognise that CRM is about to be swept away as brands and governments learn how to roll-out the algorithmic tanks.

Privacy: let’s have the right conversation

The whole social media, Big Data, privacy thing is getting an increasing amount of air time. This is good, because this is very important thing to start getting our heads around. However, I don’t think we are really yet having the right conversation.

The pre-dominant conversation out there seems to be focused on the issues concerned with the potential (and reality) of organisations (businesses or governments) ‘spying’ on citizens or consumers by collecting data on them, often without their knowledge or permission.

Our privacy is therefore being ‘invaded’.

But this is an old-fashioned, small data, definition of privacy. It assumes that the way to gain an understanding of an individual, which can then be used in a way which has consequences for that individual, is by collecting the maximum amount of information possible about them: it is about creating an accurate and comprehensive personalised data file. The more comprehensive and accurate the file is, the more useful it is. From a marketing perspective, it is the CRM way of looking at things (it is also the VRM way of looking at things, where the individual has responsibility for managing this data file).  It is also a view that then gives permission to the idea that if you detach the person from the data (i.e. make it anonymous) it stops it being used in a way which will have consequences for the individual concerned and is therefore ‘cleared’ for alternative usage.

But this is not the way that Big Data works. The ‘great’ thing about Big Data (or more specifically algorithms) is that they require almost no information about an individual in order to arrive at potentially very consequential decisions about that individual’s identity.   Instead they use ‘anonymised’ information gathered from everyone else. And increasingly this information is not just coming from other people, it is coming from things (see Internet of Things). The great thing about things is that they have no rights to privacy (yet) and they can produce more data than people.

The name of the game in the world of the algorithm is to create datafied (not digitised) maps of the world. I don’t mean literally geographical maps (although they can often have a geographical / locational component): from a marketing perspective it can be a datafied map of a product sector, or form of consumer behaviour. These maps are three dimensional in that they comprise a potentially limitless numbers of data layers. These layers can be seemingly irrelevant, inconsequential or in no way related to the sector of behaviour that is being mapped. The role of the algorithm is the stitch these layers together, so that a small piece of information in one layer can be related to all the other layers and thus find its position upon the datafied map.

In practical terms, this can mean that you can be refused a loan based on information concerning your usage of electrical appliances, as collected by your ‘smart’ electricity meter. This isn’t a scary, down-the-road sort of thing. Algorithmic lending is already here and the interesting thing about the layers in the datafied maps of algorithmic lenders is the extent to which they don’t rely on traditional ‘consequential’ information such as credit scores and credit histories. As I have said many times before, there is no such thing as inconsequential data anymore: all data has consequences.

Or to put it another way, your identity is defined by other peoples’ (or things’) data: your personal data file (i.e. your life) is simply a matter of personal opinion. It has little relevance to how the world will perceive you, no matter how factually correct or accurate it is. You are who the algorithm says you are, even if the algorithm itself has no idea why you are this (and cannot explain it if anyone comes asking) and has come to this conclusion based in no small part, by the number of times you use your kettle every day.

The world of the algorithm is a deeply scary place. That is why we need the conversation. But it needs to be the right conversation.

Astonishingly important article by Evgeny Morozov

FireShot Screen Capture #164 - 'Why the internet of things could destroy the welfare state I Technology I The Observer' - www_theguardian_com_technology_2014_jul_20_rise-of-data-death-of-politics-evgeny-morozov-algorThis is an astonishingly important article, by Evgeny Morozov, published yesterday in The Observer.  It starts to paint the picture of the world of the algorithm, drawing together the important themes that define what it is we need to be thinking and talking about so that we don’t sleep-walk into this new world – the paradoxical world where an individual’s connectedness (to other indivduals and to things) is used as a mechnism of isolation and control.

As I have said previously, the algorithm is the most powerful instrument of social control invented since the sword (and current systems of regulation are powerless against it).

http://www.socialmediatoday.com/content/sword-printing-press-and-algorithm-three-technologies-changed-world

http://richardstacy.com/2014/05/15/algorithms-growth-sensorship/

http://richardstacy.com/2014/06/27/facebook-just-dark-pool/

 

 

 

Is Facebook just a ‘dark pool’?

FireShot Screen Capture #156 - 'Barclays shares tumble after allegations about private 'dark pool' trading system I Business I The Guardian' - www_theguardian_com_business_2014_jun_26_barclays-shares-tumble-dark-poolWednesday saw an important announcement from the New York Attorney General. He announced that Barclays Bank is to be prosecuted concerning their operation of a ‘dark pool’. A dark pool is basically a private trading area which a bank can operate on behalf of its clients, or anyone else to whom the bank grants access. It is dark because it doesn’t operate to the same level of transparency as conventional exchanges. The accusation is that Barclays allowed high frequency traders into their dark pool and allowed these traders to prey on the trading activity of the other investors within the pool, including Barclays’ own clients.

This is an astonishingly important announcement for two reasons: First, it is important for Wall Street but it also important for Facebook, Google, Big Data, data protection, the Internet of Things and thus, quite possibly therefore the future of humanity itself.

First Wall Street: What is happening within Barclays’ dark pool is almost certainly similar to what is happening in the dark pools operated by almost all the major banks. It is also pretty similar to what is happening in the ‘light pools’ that constitute the official Wall Street stock exchanges (just read Michael Lewis’s ‘Flash Boys’, published a few weeks ago if you want validation of this). This will therefore be a test case and rather than go after one of the Big Beasts, the Attorney General has sensibly chosen to pick off an already wounded juvenile.   Barclays is a foreign bank, it is a peripheral player (albeit one with a very large dark pool) and it is already discredited by it actions in rigging inter-bank lending rates. It is therefore easy prey, but bringing it down will provide the ammunition necessary to tackle, or at least discipline, the major players. You can bet that there are a lot of people on Wall Street right now really focused on how this case plays out, even if the mainstream media has yet to really wake-up to its significance.

But this isn’t about just about Wall Street. What is playing out here are the first attempts to understand and regulate the world of the algorithm. High frequency trading is driven by algorithms and exploits one of an algorithm’s principle characteristics, which is its speed in processing large amounts of data. High frequency trading illustrates the power of algorithms and also their potential for abuse. High frequency trading is not illegal (yet), but it is abusive. It is only not illegal because the law makers don’t really understand how algorithms work and no-one has worked out a way to stop people who do understand them from using them in an abusive way.  Interestingly the Attorney General has not tried to establish that high frequency trading is illegal, rather that Barclays misrepresented its dark pool as offering protection from the abusive behaviour of high frequency traders.

Algorithms colonised Wall Street for two reasons: first Big Data was already there in the form of the vast amount of information flowing through the financial markets and; second, Wall Street could afford to pay top-dollar for the relatively small group of geeks who actually understand algorithms. But this is about to change. The pool of geeks is expanding and pools of data, large enough for complex algorithms to operate within, are now developing in many other places, driven by the growth of Big Data and the Internet of Things.

Which brings us to Facebook. In many ways Facebook is a dark pool, except the data within it isn’t data about financial trading, it is data about human behaviour. Now I don’t want to suggest that Facebook is trading this information or necessarily inviting access to this data for organisations who are going to behave in an abusive or predatory way. In a somewhat ironic sense of role reversal, the PRISM affair has revealed that the regulators (i.e. the NSA and the UK’s GCHQ) are the equivalent of the high frequency traders. They are the people who want to get into Facebook’s dark pool of data so they can feed it through their algorithms and Facebook has been doing what (little) it can to resist their entry. But of course there is nothing at the moment to really stop Facebook (or for that matter Google or Twitter) from allowing algorithms into their data pools. In fact, we know they are already in there. While there may not be abusive activity taking place at the moment there is nothing to stop abusive behaviour from taking place, other than the rules of integrity and behaviour that Facebook and Google set for themselves or those that might be set by the people Facebook or Google allow into their pools. Remember also that Facebook needs to generate sufficient revenue to justify a valuation north of $80 billion – and it is not going to do that simply through selling advertising, it is going to do that by selling access to its pool of data. And, of course, the growth of Big Data and the Internet of Things is creating vast data pools that exist in far more shadowy and less obvious places that Google and Facebook. This is a recipe for abusive and predatory behaviour, unless the law-makers and regulators are able to get there first and set-out the rules.

Which brings us back to New York versus Barclays. It is not just Wall Street and financial regulators who need to focus on this: this could prove to be the opening skirmish in a battle that will come to define how society will operate in the world we are now entering – the world of the algorithm. I can’t lay claim to understanding how this may play out, or how we are going to regulate the world of algorithms. The only thing I do know is that the abusive use of algorithms flourishes in the dark and the daylight of transparency is their enemy. Trying to drive a regulatory stake through the heart of every abusive algorithm is a near self-defeating exercise – far better is to create an environment where they don’t have a competitive advantage.

 

Algorithms and the growth of sensorship

Here is a quick thought.  As I have previously said, I think we are moving from the age of the printing press into the age of the algorithm.  Printing led to the growth of censorship whereas algorithms are going to lead to the growth of sensorship.

I was prompted to write this today because of the announcement that one of the UK’s largest electronic goods retailers is linking up with one of the UK’s largest mobile phone retailers.  Electronic goods are basically forms of sensor that monitor human behaviour via how they are used (note: there are now even cameras in Barbie dolls).  Mobile phone retailers basically sell connection to the internet and also provide mobile handsets, which are the most comprehensive form of personal sensor currently out there.  I heard the CEO of the new company on Radio 4’s Today programme make no bones about the fact that the underlying logic behind the deal was the growth in The Internet of Things (with electronic things being the most obvious and easy of such things to connect to the internet).

We are just at a start of a form of data detection landgrab – the Scramble for Data if you like.  Continue reading